Statistical Modeling & Machine Learning I

This is the first course in a two term sequence in applied statistical methods and machine learning that are the basis in handling complex datasets. The topics covered include: overview on the quantitative research, linear regression, analysis of variance, inference, prediction, model diagnostics and selection and resampling methods. The emphasis will be to understand and apply the methods.

Credits: 3

Course Length: Partial term

Repeatability: May not be repeated for credit.

Advisory Prerequisites: Two course sequence in probability & STATS or equivalent

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